smodels

Name	smodels JSON
Version	2.3.1 JSON
	download
home_page	https://smodels.github.io/
Summary	A tool for interpreting simplified-model results from the LHC
upload_time	2023-07-17 12:33:39
maintainer
docs_url	None
author	The SModelS collaboration, smodels-users@lists.oeaw.ac.at Current members: Mohammad Mahdi Altakach, Sabine Kraml, Andre Lessa, Sahana Narashima, Timothee Pascal, Humberto Reyes-Gonzalez, Wolfgang Waltenberger Previously involved in SModelS: Gael Alguero, Federico Ambrogi, Juhi Dutta, Jan Heisig, Charanjit K. Khosa, Suchita Kulkarni, Ursula Laa, Veronika Magerl, Wolfgang Magerl, Philipp Neuhuber, Doris Proschofsky, Jory Sonneveld, Michael Traub, Matthias Wolf, Alicia Wongel
requires_python
license	GPLv3
keywords	simplified models lhc bsm theories interpretation supersymmetry ueds
VCS
bugtrack_url
requirements	No requirements were recorded.
Travis-CI	No Travis.
coveralls test coverage	No coveralls.

            .. image:: https://smodels.github.io/pics/banner.png

.. |PyPI version| image:: https://badge.fury.io/py/smodels.svg
   :target: https://badge.fury.io/py/smodels

.. |GitHub Project| image:: https://img.shields.io/badge/GitHub--blue?style=social&logo=GitHub
   :target: https://github.com/SModelS

.. |DOI| image:: https://zenodo.org/badge/DOI/10.5281/zenodo.1169739.svg
   :target: https://doi.org/10.5281/zenodo.116973

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   :target: https://smodels.readthedocs.io

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|GitHub Project| |PyPI version| |CodeFactor| |Binder| |Docs|

==============
SModelS v2
==============

**SModelS -- A tool for interpreting simplified-model results from the LHC.**

SModelS is an automatic, public tool for interpreting simplified-model results
from the LHC. It is based on a general procedure to decompose Beyond the
Standard Model (BSM) collider signatures presenting a Z\ :sub:`2` symmetry into
Simplified Model Spectrum (SMS) topologies. Our method provides a way to cast
BSM predictions for the LHC in a model independent framework, which can be
directly confronted with the relevant experimental constraints.


Installation
============

For instructions on how to install SModelS, see
the section `Installation <http://smodels.readthedocs.io/en/latest/Installation.html>`_ of the `SModelS online manual`_.


Running SModelS
===============

SModelS provides a command-line tool (runSModelS.py) for the basic functionalities,
which can be executed as:

*./runSModelS.py -p <parameter file> -f <input file or directory> -o <output directory>*

For help instructions:

*./runSModelS.py -h*

An example file on how to call the SModelS libraries from your own
Python code can be found in *Example.py*.

Detailed explanations on how to use SModelS, including explanations of the
output, can be found in the section `Using SModelS <http://smodels.readthedocs.io/en/latest/RunningSModelS.html>`_ of the `SModelS online manual`_.

A few example input files are provided in the inputFiles folder and can be
used to test *runSModelS.py*.


Citation
========

If you use this software please cite both the SModelS v1.1_ and v1.2_ manuals,
the original_ SModelS publication, as well as the programs
it makes use of (pythia8_/pythia6_, NLL-fast_ and pyslha_).
If you use specifically the long-lived particles implementation, please cite also this_ paper.
For the Run2 database, cite the v1.2_ manual and the databaseUpdate_ paper.

For your convenience, the relevant
citations are provided in bibtex format in *references.bib*.

For citing the experimental analyses in the database, you can use
*smodels-database/database.bib*.

.. _v1.2: https://inspirehep.net/record/1705426
.. _v1.1: https://inspirehep.net/record/1510436
.. _original: https://inspirehep.net/record/1269436
.. _this: https://inspirehep.net/record/1687820
.. _databaseUpdate: https://inspirehep.net/record/1658765
.. _pythia6: https://pythia6.hepforge.org/
.. _pythia8: http://home.thep.lu.se/~torbjorn/Pythia.html
.. _pyslha: http://www.insectnation.org/projects/pyslha.html
.. _NLL-fast: http://pauli.uni-muenster.de/~akule_01/nllwiki/index.php/NLL-fast
.. _SModelS online manual: http://smodels.readthedocs.io/

            

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